Hongjian Wang

Background: A major shift in the “dynamic zero-COVID” policy was announced by China’s National Health Commission on December 7, 2022, and the subsequent immediate large-scale outbreak of SARS-CoV-2 infections in the entire country has caused worldwide concern. This observational cross-sectional study aimed to describe the epidemiological characteristics of this outbreak in Sichuan, China. Methods: All data were self-reported online by volunteers. We described the epidemic by characterizing the infection, symptoms, clinical duration, severity, spatiotemporal clustering, and dynamic features of the disease. Prevalence ratio (PR), Odds ratios (ORs) and adjusted ORs were calculated to analyze the associations between risk factors and infection and the associations of risk factors with clinical severity using log-binomial and multivariable logistic regression models; 95% confidence intervals (CIs) and Wald test results were reported. The prevalence rates and clinical severity among different subgroups were compared using the Chi-square and trend Chi-square tests. Results: Between January 6 and 12, 2023, 138,073 volunteers were enrolled in this survey, and 102,645 were infected with COVID-19, holding a prevalence rate of 74.34%; the proportion of asymptomatic infections was 1.58%. Log-binomial regression revealed that the risk of infection increased among those living in urban areas. Multivariable logistic regression analysis showed that female sex, chronic diseases, older age and the fewer doses of vaccine received were associated with an increased risk of severe clinical outcomes after infection. We estimated the mean reproduction number during this pandemic was 1.83. The highest time-dependent reproduction number was 4.15; this number decreased below 1 after 11 days from December 7, 2022. Temporal trends revealed a single peak curve with a plateau pattern of incidence during the outbreak, whereas spatiotemporal clustering analysis showed that the onset in 21 cities in the Sichuan province had four-wave peaks. Conclusions: The peak of the first wave of Omicron infection in Sichuan Province had passed and could be considered a snapshot of China under the new control strategy. There were significant increases in the risk of severe clinical outcomes after infection among females, with chronic diseases, and the elderly. The vaccines have been effective in reducing poor clinical outcomes.

Background: Serum uric acid (UA) is correlated closely with traditional cardiovascular risk factors, which might interfere with the action of UA, in patients with coronary artery disease. We performed this study to evaluate the prognostic effect of UA levels in individuals with different numbers of standard modifiable cardiovascular risk factors (SMuRFs). Methods and Results: In this prospective study, we consecutively enrolled 10 486 patients with coronary artery disease. They were stratified into 3 groups according to the tertiles of UA concentrations and, within each UA tertile, further classified into 3 groups by the number of SMuRFs (0–1 versus 2–3 versus 4). The primary end point was major adverse cardiovascular and cerebrovascular events (MACCEs), including death, myocardial infarction, stroke, and unplanned revascularization. Over a median follow‐up of 2.4 years, 1233 (11.8%) MACCEs were recorded. Patients with high UA levels developed significantly higher risk of MACCEs than those with low UA levels. In addition, UA levels were positively associated with MACCEs as a continuous variable. More importantly, in patients with 0 to 1 SMuRF, the risks of MACCEs were significantly higher in the high‐UA‐level group (adjusted hazard ratio [HR], 1.469 [95% CI, 1.197–1.804]) and medium‐UA‐level group (adjusted HR, 1.478 [95% CI, 1.012–2.160]), compared with the low‐UA‐level group, whereas no significant association was found between UA levels and the risk of MACCEs in participants with 2 to 3 or 4 SMuRFs. Conclusions: In patients with coronary artery disease who received evidence‐based secondary prevention therapies, elevated UA levels might affect the prognosis of individuals with 0 to 1 SMuRF but not that of individuals with ≥2 SMuRFs.

Background: The PRAISE (Prediction of Adverse Events Following an Acute Coronary Syndrome) score is a machine‐learning‐based model for predicting 1‐year all‐cause death, myocardial infarction, and Bleeding Academic Research Consortium (BARC) type 3/5 bleeding. Its utility in an unselected Asian population undergoing percutaneous coronary intervention for acute coronary syndrome remains unknown. We aimed to validate the PRAISE score in a real‐world Asian population. Methods and Results: A total of 6412 consecutive patients undergoing percutaneous coronary intervention for acute coronary syndrome were prospectively included. The PRAISE scores were compared with established scoring systems (GRACE [Global Registry of Acute Coronary Events] 2.0, PRECISE‐DAPT (Predicting Bleeding Complications in Patients Undergoing Stent Implantation and Subsequent Dual Antiplatelet Therapy), and PARIS [Patterns of Non‐Adherence to Anti‐Platelet Regimen in Stented Patients]) to evaluate their discrimination, calibration, and reclassification. The risk of all‐cause mortality (hazard ratio [HR], 12.24 [95% CI, 5.32–28.15]) and recurrent acute myocardial infarction (HR, 3.92 [95% CI, 1.76–8.73]) was greater in the high‐risk group than in the low‐risk group. The C‐statistics for death, myocardial infarction, and major bleeding were 0.75 (0.67–0.83), 0.61 (0.52–0.69), and 0.62 (0.46–0.77), respectively. The observed to expected ratio of death, myocardial infarction, and major bleeding was 0.427, 0.260, and 0.106, respectively. Based on the decision curve analysis, the PRAISE score displayed a slightly greater net benefit for the 1‐year risk of death (5%–10%) than the GRACE score did. Conclusions: The PRAISE score showed limited potential for risk prediction in our validation cohort with acute coronary syndrome. As a result, new prediction models or model refitting are required with improved discrimination and accuracy in risk prediction.

Background: Clinical guidelines recommend surgical intervention when left ventricular thrombus (LVT) is complicated with left ventricular aneurysm (LVA). Objectives: This study aimed to review the changes in the treatment of LVT combined with LVA over the past 12 years at our center and to compare the efficacy of medical therapy and surgical treatment on patient outcomes. Methods: Between January 2009 and June 2021, 723 patients with LVT combined with LVA were enrolled, of whom 205 received surgical ventricular reconstruction (SVR) therapy and 518 received medical therapy. The following clinical outcomes were gathered via observation: all-cause death, cardiovascular death, and major adverse cardiovascular and cerebrovascular events (MACCEs; defined as the composite of cardiovascular death, ischemic stroke, and acute myocardial infarction). The median follow-up time was 1403 [707, 2402] days. Results: The proportion of SVR dropped yearly in this group of patients, from a peak of 64.5% in 2010 to 7.5% in 2021 (p for trend < 0.001). Meanwhile, the proportion of anticoagulant use increased quickly, from 8.0% in 2016 to 67.9% in 2021 (p for trend < 0.001). The incidence rates of all-cause mortality, cardiovascular death, and MACCEs were 12.9% (n = 93), 10.5% (n = 76), and 14.7% (n = 106), respectively. In the multivariable analysis, there were no significant differences in all-cause death (HR of 0.60, 95% CI of 0.32–1.13, p = 0.11), cardiovascular death (HR of 0.79, 95% CI of 0.41–1.50, p = 0.5), and MACCEs (HR of 0.82, 95% CI of 0.49–1.38, p = 0.5) between the two groups. The competing risk regression performed in the propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) analyses was in line with the unmatched analysis. Conclusions: The rate of SVR dropped significantly among patients with both LVT and LVA, while there was an improvement in oral anticoagulant utilization. SVR with thrombus removal did not improve all-cause mortality and cardiovascular outcomes in patients with LVT and LVA. Ventricular aneurysm with thrombus may not be an indication for surgery.

Background and aims: Our goals in the study were to (1) quantify the discordance in LDL-C levels between equations (the Friedewald, Sampson, and Martin/Hopkins equations) and compare them with direct LDL-C (dLDL-C); and (2) explore the proportion of misclassified patients by calculated LDL-C using these three different equations. Methods: A total of 30,349 consecutive patients with angiographically confirmed coronary artery disease (CAD) were prospectively enrolled. Concordance was defined as if the LDL-C was <1.8 mmol/L with each pairwise comparison of LDL-C equations. Estimated LDL-C that fell into the same category as dLDL-C at the following levels: <1.4, 1.4 to 1.7, 1.8 to 2.5, 2.6 to 2.9, and ≥3.0 mmol/L was considered to have been correctly categorized. Results: The concordance was 96.3% (Sampson vs. Martin/Hopkins), 95.0% (Friedewald vs. Sampson), and 91.4% (Friedewald vs. Martin/Hopkins), respectively. This proportion fell to 82.4% in those with hypertriglyceridemia (TG ≥ 1.7 mmol/L). With an accurate classification rate of 73.6%, the Martin/Hopkins equation outperformed the Sampson equation (69.5%) and the Friedewald equation (59.3%) by a wide margin. Conclusions: Comparing it to the validated Martin/Hopkins equation, the Friedewald equation produced the lowest levels of LDL-C, followed by the Sampson equation. In the classification of LDL-C, the Martin/Hopkins equation has also been shown to be more accurate. There is a significant difference between the equations and the direct measurement method, which may lead to overtreatment or undertreatment.

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Background: In China, ischemic heart disease is the main cause of mortality. Having cardiac rehabilitation and a secondary prevention program in place is a class IA recommendation for individuals with coronary artery disease. WeChat-based interventions seem to be feasible and efficient for the follow-up and management of chronic diseases. Objective: This study aims to evaluate the effectiveness of a tertiary A-level hospital, WeChat-based telemedicine intervention in comparison with conventional community hospital follow-up on medication adherence and risk factor control in individuals with stable coronary artery disease. Methods: In this multicenter prospective study, 1424 patients with stable coronary artery disease in Beijing, China, were consecutively enrolled between September 2018 and September 2019 from the Fuwai Hospital and 4 community hospitals. At 1-, 3-, 6-, and 12-month follow-up, participants received healthy lifestyle recommendations and medication advice. Subsequently, the control group attended an offline outpatient clinic at 4 separate community hospitals. The intervention group had follow-up visits through WeChat-based telemedicine management. The main end point was medication adherence, which was defined as participant compliance in taking all 4 cardioprotective medications that would improve the patient’s outcome (therapies included antiplatelet therapy, β-blockers, statins, and angiotensin-converting-enzyme inhibitors or angiotensin-receptor blockers). Multivariable generalized estimating equations were used to compare the primary and secondary outcomes between the 2 groups and to calculate the relative risk (RR) at 12 months. Propensity score matching and inverse probability of treatment weighting were performed as sensitivity analyses, and propensity scores were calculated using a multivariable logistic regression model. Results: At 1 year, 88% (565/642) of patients in the intervention group and 91.8% (518/564) of patients in the control group had successful follow-up data. We matched 257 pairs of patients between the intervention and control groups. There was no obvious advantage in medication adherence with the 4 cardioprotective drugs in the intervention group (172/565, 30.4%, vs 142/518, 27.4%; RR 0.99, 95% CI 0.97-1.02; P=.65). The intervention measures improved smoking cessation (44/565, 7.8%, vs 118/518, 22.8%; RR 0.48, 95% CI 0.44-0.53; P<.001) and alcohol restriction (33/565, 5.8%, vs 91/518, 17.6%; RR 0.47, 95% CI 0.42-0.54; P<.001). Conclusions: The tertiary A-level hospital, WeChat-based intervention did not improve adherence to the 4 cardioprotective medications compared with the traditional method. Tertiary A-level hospital, WeChat-based interventions have a positive effect on improving lifestyle, such as quitting drinking and smoking, in patients with stable coronary artery disease and can be tried as a supplement to community hospital follow-up. Trial Registration: ClinicalTrials.gov NCT04795505; https://clinicaltrials.gov/ct2/show/NCT04795505

BACKGROUND In China, ischemic heart disease is the main cause of mortality. Having cardiac rehabilitation and a secondary prevention program in place is a class IA recommendation for individuals with coronary artery disease. WeChat-based interventions seem to be feasible and efficient for the follow-up and management of chronic diseases. OBJECTIVE This study aims to evaluate the effectiveness of a tertiary A-level hospital, WeChat-based telemedicine intervention in comparison with conventional community hospital follow-up on medication adherence and risk factor control in individuals with stable coronary artery disease. METHODS In this multicenter prospective study, 1424 patients with stable coronary artery disease in Beijing, China, were consecutively enrolled between September 2018 and September 2019 from the Fuwai Hospital and 4 community hospitals. At 1-, 3-, 6-, and 12-month follow-up, participants received healthy lifestyle recommendations and medication advice. Subsequently, the control group attended an offline outpatient clinic at 4 separate community hospitals. The intervention group had follow-up visits through WeChat-based telemedicine management. The main end point was medication adherence, which was defined as participant compliance in taking all 4 cardioprotective medications that would improve the patient’s outcome (therapies included antiplatelet therapy, β-blockers, statins, and angiotensin-converting-enzyme inhibitors or angiotensin-receptor blockers). Multivariable generalized estimating equations were used to compare the primary and secondary outcomes between the 2 groups and to calculate the relative risk (RR) at 12 months. Propensity score matching and inverse probability of treatment weighting were performed as sensitivity analyses, and propensity scores were calculated using a multivariable logistic regression model. RESULTS At 1 year, 88% (565/642) of patients in the intervention group and 91.8% (518/564) of patients in the control group had successful follow-up data. We matched 257 pairs of patients between the intervention and control groups. There was no obvious advantage in medication adherence with the 4 cardioprotective drugs in the intervention group (172/565, 30.4%, vs 142/518, 27.4%; RR 0.99, 95% CI 0.97-1.02; P=.65). The intervention measures improved smoking cessation (44/565, 7.8%, vs 118/518, 22.8%; RR 0.48, 95% CI 0.44-0.53; P<.001) and alcohol restriction (33/565, 5.8%, vs 91/518, 17.6%; RR 0.47, 95% CI 0.42-0.54; P<.001). CONCLUSIONS The tertiary A-level hospital, WeChat-based intervention did not improve adherence to the 4 cardioprotective medications compared with the traditional method. Tertiary A-level hospital, WeChat-based interventions have a positive effect on improving lifestyle, such as quitting drinking and smoking, in patients with stable coronary artery disease and can be tried as a supplement to community hospital follow-up. CLINICALTRIAL ClinicalTrials.gov NCT04795505; https://clinicaltrials.gov/ct2/show/NCT04795505

Gambogic acid (GA) has been shown to inhibit cancer cell proliferation, induce apoptosis, and enhance reactive oxygen species accumulation. However, whether GA could improve multidrug resistance through modulating autophagy has never been explored. We demonstrated that the combination of GA and cisplatin (CDDP) resulted in a stronger growth inhibition effect on A549 and NCI‐H460 cells using the MTT assay. Furthermore, treatment with GA significantly increased autophagy in these cells. More importantly, GA‐induced cell death could be largely abolished by 3‐methyladenine (3‐MA) or chloroquine (CQ) treatment, suggesting that GA‐induced cell death was dependent on autophagy. Western blot analysis showed that GA treatment suppressed the activation of Akt, mTOR, and S6. In addition, using a GA and rapamycin combination induced more cell death compared to either GA or rapamycin alone. In summary, GA may have utility as an adjunct therapy for non‐small cell lung cancer (NSCLC) patients through autophagy‐dependent cell death, even when cancer cells have developed resistance to apoptosis.